Heavy alcohol consumption is associated with alcohol use disorders (AUDs), an increased risk of cirrhosis, certain types of cancers, cardiovascular disease, and cognitive disorders. Drinking above the NIAAA- recommended maximum safe limits, no more than 4 drinks per day and 14 per week for men and no more than 3 drinks per day and 7 drinks per week for women, is associated with alcohol-related harm. Yet, moderate levels of alcohol consumption, that is, 2 or less drinks per day, are associated with a decreased risk of myocardial infarction and cardiac mortality compared to non-drinkers. Thus, understanding the mechanisms that influence levels of alcohol consumption is an important public health concern and can lead to improved treatments and public health interventions to reduce heavy alcohol use and improve health outcomes. There is strong evidence that both genetic and environmental factors play a role in determining an individual's alcohol use, including alcohol consumption and alcohol dependence. Several genome-wide association studies of alcohol dependence and alcohol consumption have recently been published, identifying promising candidates for further investigation in additional large study populations. Expanding sample size for genetic studies often requires combining data from different studies, which may have been ascertained using different criteria, different phenotype measurements, and different genotyping platforms. Each of these differences can lead to heterogeneity in effects and limit power to detect and confirm associations. Conducting a genome-wide association study in a single, large sample with harmonized phenotype collection is a powerful method for investigating the effect of genetic variation on alcohol consumption. We will leverage existing genotype data on 100,000 subjects from the Kaiser Permanente (KP) Research Program on Genes, Environment, and Health (RPGEH) to conduct a genome-wide association study of alcohol consumption. We propose the following specific aims: Aim 1: To identify genetic variants associated with drinking frequency among drinkers. Aim 2: To identify genetic variants associated with typical quantity of alcohol consumed in a day. Aim 3: To identify genetic variants associated with exceeding NIAAA-defined safe drinking limits. The RPGEH cohort is an ideal sample in which to conduct these analyses because it is a single, large cohort with available genotype data and alcohol-related phenotype information collected using a single, consistent questionnaire.